[dsp EDUCATION] Research Developments and Directions in Speech Recognition and Understanding, Part 1

[dsp EDUCATION] Research Developments and Directions in Speech Recognition and Understanding, Part 1

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by Janet M. Baker , Li Deng , James Glass , Sanjeev Khudanpur , Chin-hui Lee , Nelson Morgan

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TITLE	[dsp EDUCATION] Research Developments and Directions in Speech Recognition and Understanding, Part 1	SVM HeaderParse 0.2
AUTHOR NAME	Janet M. Baker	SVM HeaderParse 0.2
AUTHOR AFFIL	Douglas O’Shaughnessy	SVM HeaderParse 0.2
AUTHOR NAME	Li Deng	SVM HeaderParse 0.2
AUTHOR NAME	James Glass	SVM HeaderParse 0.2
AUTHOR NAME	Sanjeev Khudanpur	SVM HeaderParse 0.2
AUTHOR NAME	Chin-hui Lee	SVM HeaderParse 0.2
AUTHOR NAME	Nelson Morgan	SVM HeaderParse 0.2
AUTHOR AFFIL	SIGNIFICANT DEVELOPMENTS; IN SPEECH RECOGNITION; AND UNDERSTANDING	SVM HeaderParse 0.2
ABSTRACT	To advance research, it is important to identify promising future research directions, especially those that have not been adequately pursued or funded in the past. The working group producing this article was charged to elicit from the human language technology (HLT) community a set of well-considered directions or rich areas for future research that could lead to major paradigm shifts in the field of automatic speech recognition (ASR) and understanding. ASR has been an area of great interest and activity to the signal processing and HLT communities over the past several decades. As a first step, this group reviewed major developments in the field and the circumstances that led to their success and then focused on areas it deemed especially fertile for future research. Part 1 of this article will focus on historically significant developments in the ASR area, including several major research efforts that were guided by different funding agencies, and suggest general areas in which to focus research. Part 2 (to appear in the next issue) will explore in more detail several new avenues holding promise for substantial improvements in ASR performance. These entail cross-disciplinary research and specific approaches to address three-to-five-year grand challenges aimed at stimulating advanced research by dealing with realistic tasks of broad interest.	SVM HeaderParse 0.2
CITATIONS	51 found	ParsCit 1.0